Dynamic customer interdependence

Abstract

In managing today’s customer base, firms need to consider not only interactions with customers but also interactions among customers. Much like the interactions between customers and firms, the interactions among customers are dynamic in nature and thus create a dynamic structure of preference interdependencies between customers. This research proposes a Bayesian spatio-temporal model that simultaneously captures the effects of the interactions between customers and the firm, the static interdependence due to customers’ inherent similarities, and the dynamic interdependence arising from observed interactions among customers. The model is applied to a rich dataset of university alumni donation and event attendance spanning 27 years. The results yield significant static and dynamic interdependence among the group as well as synergistic effects between static and dynamic structures. This research demonstrates that not accounting for such interdependence, when such interdependence exists, would provide a biased view of firms' marketing effectiveness, yield inferior prediction of customer behaviors in group settings, and miss opportunities to develop group marketing strategies.